End of training

README.md

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+---
+base_model: stabilityai/stable-diffusion-3-medium-diffusers
+library_name: diffusers
+license: openrail++
+tags:
+- text-to-image
+- diffusers-training
+- diffusers
+- lora
+- sd3
+- sd3-diffusers
+- template:sd-lora
+instance_prompt: photo of a nobcap can
+widget: []
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# SD3 DreamBooth LoRA - Kvisten/output
+
+<Gallery />
+
+## Model description
+
+These are Kvisten/output DreamBooth LoRA weights for stabilityai/stable-diffusion-3-medium-diffusers.
+
+The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
+
+Was LoRA for the text encoder enabled? True.
+
+## Trigger words
+
+You should use `photo of a nobcap can` to trigger the image generation.
+
+## Download model
+
+[Download the *.safetensors LoRA](Kvisten/output/tree/main) in the Files & versions tab.
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-3-medium-diffusers', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('Kvisten/output', weight_name='pytorch_lora_weights.safetensors')
+image = pipeline('photo of a nobcap can').images[0]
+```
+
+### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
+
+- **LoRA**: download **[`diffusers_lora_weights.safetensors` here 💾](/Kvisten/output/blob/main/diffusers_lora_weights.safetensors)**.
+    - Rename it and place it on your `models/Lora` folder.
+    - On AUTOMATIC1111, load the LoRA by adding `<lora:your_new_name:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
+
+For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
+
+## License
+
+Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE).
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]

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+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.0001
+adam_weight_decay_text_encoder: 0.001
+allow_tf32: false
+cache_dir: null
+caption_column: null
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+checkpointing_steps: 200
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+class_data_dir: /content/data/class_images
+class_prompt: photo of a can
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+gradient_checkpointing: true
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+instance_prompt: photo of a nobcap can
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+logging_dir: logs
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+logit_std: 1.0
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+lr_power: 1.0
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+lr_warmup_steps: 0
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+max_sequence_length: 77
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+mixed_precision: fp16
+mode_scale: 1.29
+num_class_images: 50
+num_train_epochs: 16
+num_validation_images: 4
+optimizer: AdamW
+output_dir: output
+precondition_outputs: 1
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+validation_prompt: null
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